T2D - Liver

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Last updated: 2022-02-26

Checks: 6 1

Knit directory: cTWAS_analysis/

This reproducible R Markdown analysis was created with workflowr (version 1.6.2). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

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absolute	relative
/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/	data
/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/code/ctwas_config.R	code/ctwas_config.R

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Ignored files:
    Ignored:    .ipynb_checkpoints/
    Ignored:    data/AF/

Untracked files:
    Untracked:  Rplot.png
    Untracked:  analysis/.ipynb_checkpoints/
    Untracked:  analysis/Glucose_Adipose_Subcutaneous.Rmd
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    Untracked:  code/run_LDL_analysis_S.sh
    Untracked:  code/run_LDL_ctwas_rss_LDR_S.R
    Untracked:  code/run_T2D_analysis.sbatch
    Untracked:  code/run_T2D_analysis.sh
    Untracked:  code/run_T2D_ctwas_rss_LDR.R
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Unstaged changes:
    Modified:   analysis/BMI_Brain_Amygdala_S.Rmd
    Modified:   analysis/BMI_Brain_Anterior_cingulate_cortex_BA24_S.Rmd
    Modified:   analysis/BMI_Brain_Caudate_basal_ganglia_S.Rmd
    Modified:   analysis/BMI_Brain_Cerebellar_Hemisphere_S.Rmd
    Modified:   analysis/BMI_Brain_Cerebellum_S.Rmd
    Modified:   analysis/BMI_Brain_Cortex.Rmd
    Modified:   analysis/BMI_Brain_Cortex_S.Rmd
    Modified:   analysis/BMI_Brain_Frontal_Cortex_BA9_S.Rmd
    Modified:   analysis/BMI_Brain_Hippocampus_S.Rmd
    Modified:   analysis/BMI_Brain_Hypothalamus_S.Rmd
    Modified:   analysis/BMI_Brain_Nucleus_accumbens_basal_ganglia_S.Rmd
    Modified:   analysis/BMI_Brain_Putamen_basal_ganglia_S.Rmd
    Modified:   analysis/BMI_Brain_Spinal_cord_cervical_c-1_S.Rmd
    Modified:   analysis/BMI_Brain_Substantia_nigra_S.Rmd
    Modified:   analysis/LDL_Liver_S.Rmd

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Weight QC

#number of imputed weights
nrow(qclist_all)

[1] 6749

#number of imputed weights by chromosome
table(qclist_all$chr)

  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18  19  20 
693 529 449 280 351 381 339 268 267 299 405 423 131 247 240 250 343 112 336 180 
 21  22 
 67 159 

#number of imputed weights without missing variants
sum(qclist_all$nmiss==0)

[1] 4358

#proportion of imputed weights without missing variants
mean(qclist_all$nmiss==0)

[1] 0.6457

Check convergence of parameters

Past versions of unnamed-chunk-5-1.png

Version	Author	Date
0974c69	sq-96	2022-02-14
e6bc169	sq-96	2022-02-13

#estimated group prior
estimated_group_prior <- group_prior_rec[,ncol(group_prior_rec)]
names(estimated_group_prior) <- c("gene", "snp")
estimated_group_prior["snp"] <- estimated_group_prior["snp"]*thin #adjust parameter to account for thin argument
print(estimated_group_prior)

     gene       snp 
0.0121777 0.0003704 

#estimated group prior variance
estimated_group_prior_var <- group_prior_var_rec[,ncol(group_prior_var_rec)]
names(estimated_group_prior_var) <- c("gene", "snp")
print(estimated_group_prior_var)

 gene   snp 
8.728 8.899 

#report sample size
print(sample_size)

[1] 62892

#report group size
group_size <- c(nrow(ctwas_gene_res), n_snps)
print(group_size)

[1]    6749 5017190

#estimated group PVE
estimated_group_pve <- estimated_group_prior_var*estimated_group_prior*group_size/sample_size #check PVE calculation
names(estimated_group_pve) <- c("gene", "snp")
print(estimated_group_pve)

   gene     snp 
0.01141 0.26295 

#compare sum(PIP*mu2/sample_size) with above PVE calculation
c(sum(ctwas_gene_res$PVE),sum(ctwas_snp_res$PVE))

[1] 0.06078 1.45686

Genes with highest PIPs

Past versions of unnamed-chunk-7-1.png

Version	Author	Date
0974c69	sq-96	2022-02-14

           genename region_tag susie_pip   mu2       PVE      z num_eqtl
5632          CAND2        3_9    0.8555 22.92 0.0003117 -4.854        1
7788        NCKAP5L      12_31    0.8257 27.05 0.0003551  5.000        1
3444          GTF3A       13_7    0.7913 23.01 0.0002896 -4.478        2
11216       CYP21A2       6_26    0.7664 38.72 0.0004718  7.835        1
11883 RP11-209K10.2      15_22    0.7522 27.46 0.0003284 -5.056        1
7394       TP53INP1       8_66    0.7463 25.33 0.0003006 -5.474        1
6171        ARL14EP      11_21    0.7361 22.13 0.0002590 -4.512        3
10272         PARVA       11_9    0.7148 21.99 0.0002500  3.862        1
3551         KBTBD4      11_29    0.7095 26.51 0.0002990 -5.098        1
2050         DNASE2      19_10    0.7071 19.19 0.0002157 -3.744        1
4127         ZNF236      18_45    0.6921 20.89 0.0002298 -4.378        1
8335         CLSTN1        1_7    0.6180 20.20 0.0001985  3.978        1
6831           RPL8       8_94    0.6080 26.54 0.0002566 -5.063        1
1320        CWF19L1      10_64    0.5714 32.84 0.0002984 -5.742        2
9797          SLIT1      10_62    0.5606 23.74 0.0002116  4.762        1
6558          AP3S2      15_41    0.5570 39.32 0.0003483  6.483        1
8968         ALS2CL       3_33    0.5364 22.70 0.0001936  3.405        1
5574          MRPS5       2_57    0.5288 22.15 0.0001862 -3.737        1
11765 RP11-110I1.12      11_71    0.5256 18.71 0.0001563  3.747        1
5773          CRIP3       6_33    0.5254 21.27 0.0001777  4.511        2

Genes with largest effect sizes

Past versions of unnamed-chunk-8-1.png

Version	Author	Date
0974c69	sq-96	2022-02-14

           genename region_tag susie_pip   mu2       PVE      z num_eqtl
9887        NCR3LG1      11_12   0.02703 67.63 2.907e-05 -8.447        2
12661     LINC01126       2_27   0.03031 54.49 2.626e-05 -8.377        1
6291          JAZF1       7_23   0.01529 42.70 1.038e-05 -6.628        1
9311         UBE2E2       3_17   0.45738 39.65 2.883e-04  6.058        2
6558          AP3S2      15_41   0.55702 39.32 3.483e-04  6.483        1
6667          UBE2Z      17_28   0.05352 39.28 3.343e-05 -6.797        1
10351      TMEM229B      14_32   0.27272 38.81 1.683e-04 -3.685        2
11216       CYP21A2       6_26   0.76639 38.72 4.718e-04  7.835        1
4550          P2RX4      12_74   0.19404 38.50 1.188e-04  4.087        1
2084          RASA4       7_63   0.14390 33.96 7.771e-05 -4.470        1
10830       SYNJ2BP      14_32   0.15324 33.12 8.070e-05 -3.228        1
1320        CWF19L1      10_64   0.57140 32.84 2.984e-04 -5.742        2
2887          NRBP1       2_16   0.02462 32.74 1.281e-05 -5.595        1
6867          FMNL3      12_31   0.17840 32.21 9.137e-05  3.719        1
6223         GPR180      13_47   0.20330 31.88 1.030e-04 -3.353        1
8847        CCDC121       2_16   0.13639 31.87 6.912e-05  3.505        1
6456           ART3       4_51   0.22417 31.82 1.134e-04 -3.686        2
191           CEP68       2_42   0.50066 31.63 2.518e-04  6.229        2
7489        SDCCAG3       9_73   0.31043 31.39 1.549e-04 -3.739        2
9802  RP11-195F19.5       9_27   0.36489 31.33 1.818e-04 -3.408        2

Genes with highest PVE

           genename region_tag susie_pip   mu2       PVE      z num_eqtl
11216       CYP21A2       6_26    0.7664 38.72 0.0004718  7.835        1
7788        NCKAP5L      12_31    0.8257 27.05 0.0003551  5.000        1
6558          AP3S2      15_41    0.5570 39.32 0.0003483  6.483        1
11883 RP11-209K10.2      15_22    0.7522 27.46 0.0003284 -5.056        1
5632          CAND2        3_9    0.8555 22.92 0.0003117 -4.854        1
7394       TP53INP1       8_66    0.7463 25.33 0.0003006 -5.474        1
3551         KBTBD4      11_29    0.7095 26.51 0.0002990 -5.098        1
1320        CWF19L1      10_64    0.5714 32.84 0.0002984 -5.742        2
3444          GTF3A       13_7    0.7913 23.01 0.0002896 -4.478        2
9311         UBE2E2       3_17    0.4574 39.65 0.0002883  6.058        2
6171        ARL14EP      11_21    0.7361 22.13 0.0002590 -4.512        3
6831           RPL8       8_94    0.6080 26.54 0.0002566 -5.063        1
191           CEP68       2_42    0.5007 31.63 0.0002518  6.229        2
10272         PARVA       11_9    0.7148 21.99 0.0002500  3.862        1
3522        BHLHE41      12_18    0.4800 30.18 0.0002304  5.640        1
4127         ZNF236      18_45    0.6921 20.89 0.0002298 -4.378        1
2050         DNASE2      19_10    0.7071 19.19 0.0002157 -3.744        1
9797          SLIT1      10_62    0.5606 23.74 0.0002116  4.762        1
10501        MAP3K3      17_37    0.4887 26.31 0.0002045 -5.170        1
8335         CLSTN1        1_7    0.6180 20.20 0.0001985  3.978        1

Genes with largest z scores

       genename region_tag susie_pip   mu2       PVE      z num_eqtl
9887    NCR3LG1      11_12   0.02703 67.63 2.907e-05 -8.447        2
12661 LINC01126       2_27   0.03031 54.49 2.626e-05 -8.377        1
11216   CYP21A2       6_26   0.76639 38.72 4.718e-04  7.835        1
6667      UBE2Z      17_28   0.05352 39.28 3.343e-05 -6.797        1
6291      JAZF1       7_23   0.01529 42.70 1.038e-05 -6.628        1
6558      AP3S2      15_41   0.55702 39.32 3.483e-04  6.483        1
191       CEP68       2_42   0.50066 31.63 2.518e-04  6.229        2
9311     UBE2E2       3_17   0.45738 39.65 2.883e-04  6.058        2
10639      MICB       6_25   0.38273 28.87 1.757e-04  5.917        1
1320    CWF19L1      10_64   0.57140 32.84 2.984e-04 -5.742        2
3522    BHLHE41      12_18   0.48002 30.18 2.304e-04  5.640        1
2887      NRBP1       2_16   0.02462 32.74 1.281e-05 -5.595        1
11110       LTA       6_25   0.04071 27.69 1.793e-05  5.500        1
7394   TP53INP1       8_66   0.74634 25.33 3.006e-04 -5.474        1
326    ATP6V0A1      17_25   0.11561 26.56 4.882e-05  5.188        2
10501    MAP3K3      17_37   0.48875 26.31 2.045e-04 -5.170        1
3848     TSPAN8      12_44   0.24678 27.07 1.062e-04  5.137        1
3551     KBTBD4      11_29   0.70951 26.51 2.990e-04 -5.098        1
10594     PSMB8       6_27   0.20581 27.99 9.160e-05  5.081        1
6831       RPL8       8_94   0.60805 26.54 2.566e-04 -5.063        1

Comparing z scores and PIPs

Past versions of unnamed-chunk-11-1.png

Version	Author	Date
0974c69	sq-96	2022-02-14

Past versions of unnamed-chunk-11-2.png

Version	Author	Date
0974c69	sq-96	2022-02-14

[1] 0.006075

       genename region_tag susie_pip   mu2       PVE      z num_eqtl
9887    NCR3LG1      11_12   0.02703 67.63 2.907e-05 -8.447        2
12661 LINC01126       2_27   0.03031 54.49 2.626e-05 -8.377        1
11216   CYP21A2       6_26   0.76639 38.72 4.718e-04  7.835        1
6667      UBE2Z      17_28   0.05352 39.28 3.343e-05 -6.797        1
6291      JAZF1       7_23   0.01529 42.70 1.038e-05 -6.628        1
6558      AP3S2      15_41   0.55702 39.32 3.483e-04  6.483        1
191       CEP68       2_42   0.50066 31.63 2.518e-04  6.229        2
9311     UBE2E2       3_17   0.45738 39.65 2.883e-04  6.058        2
10639      MICB       6_25   0.38273 28.87 1.757e-04  5.917        1
1320    CWF19L1      10_64   0.57140 32.84 2.984e-04 -5.742        2
3522    BHLHE41      12_18   0.48002 30.18 2.304e-04  5.640        1
2887      NRBP1       2_16   0.02462 32.74 1.281e-05 -5.595        1
11110       LTA       6_25   0.04071 27.69 1.793e-05  5.500        1
7394   TP53INP1       8_66   0.74634 25.33 3.006e-04 -5.474        1
326    ATP6V0A1      17_25   0.11561 26.56 4.882e-05  5.188        2
10501    MAP3K3      17_37   0.48875 26.31 2.045e-04 -5.170        1
3848     TSPAN8      12_44   0.24678 27.07 1.062e-04  5.137        1
3551     KBTBD4      11_29   0.70951 26.51 2.990e-04 -5.098        1
10594     PSMB8       6_27   0.20581 27.99 9.160e-05  5.081        1
6831       RPL8       8_94   0.60805 26.54 2.566e-04 -5.063        1

Gene set enrichment for genes with PIP>0.5

[1] 21

Uploading data to Enrichr... Done.
  Querying GO_Biological_Process_2021... Done.
  Querying GO_Cellular_Component_2021... Done.
  Querying GO_Molecular_Function_2021... Done.
Parsing results... Done.
[1] "GO_Biological_Process_2021"

Past versions of unnamed-chunk-12-1.png

Version	Author	Date
0974c69	sq-96	2022-02-14

[1] Term             Overlap          Adjusted.P.value Genes           
<0 rows> (or 0-length row.names)
[1] "GO_Cellular_Component_2021"

Past versions of unnamed-chunk-12-2.png

Version	Author	Date
0974c69	sq-96	2022-02-14

[1] Term             Overlap          Adjusted.P.value Genes           
<0 rows> (or 0-length row.names)
[1] "GO_Molecular_Function_2021"

[1] Term             Overlap          Adjusted.P.value Genes           
<0 rows> (or 0-length row.names)
                                                           Description     FDR
22                           Late onset congenital adrenal hyperplasia 0.01134
32 Hyperandrogenism, Nonclassic Type, due to 21-Hydroxylase Deficiency 0.01134
34     Congenital adrenal hyperplasia due to 21 hydroxylase deficiency 0.01134
38                      SPINOCEREBELLAR ATAXIA, AUTOSOMAL RECESSIVE 17 0.01134
1                                       Congenital adrenal hyperplasia 0.05394
2                                                  Atrial Fibrillation 0.05394
8                            Glomerulonephritis, Membranoproliferative 0.05394
19                                      Paroxysmal atrial fibrillation 0.05394
33                                      Persistent atrial fibrillation 0.05394
35                                        familial atrial fibrillation 0.05394
   Ratio  BgRatio
22  1/11   1/9703
32  1/11   1/9703
34  1/11   1/9703
38  1/11   1/9703
1   1/11   9/9703
2   2/11 160/9703
8   1/11   7/9703
19  2/11 156/9703
33  2/11 156/9703
35  2/11 156/9703
Loading the functional categories...
Loading the ID list...
Loading the reference list...
Performing the enrichment analysis...

Warning in oraEnrichment(interestGeneList, referenceGeneList, geneSet, minNum =
minNum, : No significant gene set is identified based on FDR 0.05!

Past versions of unnamed-chunk-12-3.png

Version	Author	Date
0974c69	sq-96	2022-02-14

NULL

PIP Manhattan Plot

Past versions of unnamed-chunk-13-1.png

Version	Author	Date
0974c69	sq-96	2022-02-14

Sensitivity, specificity and precision for silver standard genes

#number of genes in known annotations
print(length(known_annotations))

[1] 72

#number of genes in known annotations with imputed expression
print(sum(known_annotations %in% ctwas_gene_res$genename))

[1] 20

#significance threshold for TWAS
print(sig_thresh)

[1] 4.482

#number of ctwas genes
length(ctwas_genes)

[1] 21

#number of TWAS genes
length(twas_genes)

[1] 41

#show novel genes (ctwas genes with not in TWAS genes)
ctwas_gene_res[ctwas_gene_res$genename %in% novel_genes,report_cols]

           genename region_tag susie_pip   mu2       PVE      z num_eqtl
8335         CLSTN1        1_7    0.6180 20.20 0.0001985  3.978        1
5574          MRPS5       2_57    0.5288 22.15 0.0001862 -3.737        1
8968         ALS2CL       3_33    0.5364 22.70 0.0001936  3.405        1
10272         PARVA       11_9    0.7148 21.99 0.0002500  3.862        1
11765 RP11-110I1.12      11_71    0.5256 18.71 0.0001563  3.747        1
4127         ZNF236      18_45    0.6921 20.89 0.0002298 -4.378        1
2050         DNASE2      19_10    0.7071 19.19 0.0002157 -3.744        1
3444          GTF3A       13_7    0.7913 23.01 0.0002896 -4.478        2

#sensitivity / recall
print(sensitivity)

ctwas  TWAS 
    0     0 

#specificity
print(specificity)

 ctwas   TWAS 
0.9969 0.9939 

#precision / PPV
print(precision)

ctwas  TWAS 
    0     0 

Past versions of unnamed-chunk-16-1.png

Version	Author	Date
0974c69	sq-96	2022-02-14

Session information

sessionInfo()

R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] readxl_1.3.1      forcats_0.5.1     stringr_1.4.0     dplyr_1.0.7      
 [5] purrr_0.3.4       readr_2.1.1       tidyr_1.1.4       tidyverse_1.3.1  
 [9] tibble_3.1.6      WebGestaltR_0.4.4 disgenet2r_0.99.2 enrichR_3.0      
[13] cowplot_1.0.0     ggplot2_3.3.5     workflowr_1.6.2  

loaded via a namespace (and not attached):
 [1] fs_1.5.2          lubridate_1.8.0   bit64_4.0.5       doParallel_1.0.17
 [5] httr_1.4.2        rprojroot_2.0.2   tools_3.6.1       backports_1.4.1  
 [9] doRNG_1.8.2       utf8_1.2.2        R6_2.5.1          vipor_0.4.5      
[13] DBI_1.1.2         colorspace_2.0-2  withr_2.4.3       ggrastr_1.0.1    
[17] tidyselect_1.1.1  bit_4.0.4         curl_4.3.2        compiler_3.6.1   
[21] git2r_0.26.1      rvest_1.0.2       cli_3.1.0         Cairo_1.5-12.2   
[25] xml2_1.3.3        labeling_0.4.2    scales_1.1.1      apcluster_1.4.8  
[29] digest_0.6.29     rmarkdown_2.11    svglite_1.2.2     pkgconfig_2.0.3  
[33] htmltools_0.5.2   dbplyr_2.1.1      fastmap_1.1.0     highr_0.9        
[37] rlang_1.0.1       rstudioapi_0.13   RSQLite_2.2.8     jquerylib_0.1.4  
[41] farver_2.1.0      generics_0.1.1    jsonlite_1.7.2    vroom_1.5.7      
[45] magrittr_2.0.2    Matrix_1.2-18     ggbeeswarm_0.6.0  Rcpp_1.0.8       
[49] munsell_0.5.0     fansi_1.0.2       gdtools_0.1.9     lifecycle_1.0.1  
[53] stringi_1.7.6     whisker_0.3-2     yaml_2.2.1        plyr_1.8.6       
[57] grid_3.6.1        blob_1.2.2        ggrepel_0.9.1     parallel_3.6.1   
[61] promises_1.0.1    crayon_1.5.0      lattice_0.20-38   haven_2.4.3      
[65] hms_1.1.1         knitr_1.36        pillar_1.6.4      igraph_1.2.10    
[69] rjson_0.2.20      rngtools_1.5.2    reshape2_1.4.4    codetools_0.2-16 
[73] reprex_2.0.1      glue_1.6.2        evaluate_0.14     data.table_1.14.2
[77] modelr_0.1.8      vctrs_0.3.8       tzdb_0.2.0        httpuv_1.5.1     
[81] foreach_1.5.2     cellranger_1.1.0  gtable_0.3.0      assertthat_0.2.1 
[85] cachem_1.0.6      xfun_0.29         broom_0.7.10      later_0.8.0      
[89] iterators_1.0.14  beeswarm_0.2.3    memoise_2.0.1     ellipsis_0.3.2